Sand corrosion,thermal expansion,and ablation of medium- and high-entropy compositionally complex fluorite oxides

Sand corrosion, thermal expansion, and ablation properties of a new class of medium- and high-entropy compositionally complex fluorite oxides (CCFOs) are examined as potential protective coating materials. Five binary oxides were mixed and sintered into dense, single-phase CCFOs of the general formula: [Hf_(1-2x)/3Zr_(1-2x)/3Ce_(1-2x)/3Y_xYb_x]O_2-δ (x = 0.2, 0.074, and 0.029). These CCFOs exhibit decreased molten sand infiltration and interaction at intermediate temperatures (1200-1300°C) in comparison with a cubic yttria-stabilized zirconia (YSZ) reference; however, at higher temperatures, the trend is reversed due to the increased chemical reactivity. The equimolar high-entropy (Hf_0.2Zr_0.2Ce_0.2Y_0.2Yb_0.2)O_2-δ exhibits no grain boundary penetration by molten sand at all examined temperatures (1200°C-1500°C), although reaction and precipitation are significant. Moreover, these CCFOs exhibit higher intrinsic thermal expansion coefficients (CTE) than the YSZ reference, thereby being more compatible with Ni-based superalloys. The 8YSZ-like (Hf_0.284Zr_0.284Ce_0.284Y_0.074Yb_0.074)O_2-δ exhibits the highest CTE in this series of CCFOs due to oxygen clustering effects. Finally, these CCFOs also exhibit lower emissivities and form unique faceted microstructures in ablative environments.     

Improved authentication and computation of medical data transmission in the secure IoT using hyperelliptic curve cryptography

The Journal of Supercomputing - Data transmission is a great challenge in any network environment. However, medical data collected from IoT devices need to be transmitted at high speed to ensure...     

Experiencing flow with instant messaging and its facilitating role on creative behaviors

The goal of this study is to explore how experiencing flow with IM, an Internet-based communication technology, can facilitate an individual’s perception on creativity. We argue that certain capabilities in IM, telepresence and perceived control, provide users a means to experience flow. We further investigate whether flow and its outcomes, positive affect and exploratory behavior have any influence on the perception of creativity of the users. Using an online survey with 207 observations we found that user’s perceived control over the technology and its ability to transport the user to a virtual environment were shown to facilitate the experience of flow. We found that flow in itself does not influence perceived expected creativity in its users but does indirectly influence perceived expected creativity through exploratory behavior and positive affect. From these initial findings we believe that our study provides implications for both users and designers on IT. Furthermore, managers can apply the findings during implementation and use of interactive information technologies for communications in the workplace.     

Application of extreme learning machine for series compensated transmission line protection

This paper proposes a new approach based on combined Wavelet Transform-Extreme Learning Machine (WT-ELM) technique for fault section identification (whether the fault is before or after the series capacitor as observed from the relay point), classification and location in a series compensated transmission line. This method uses the samples of fault currents for half cycle duration from the inception of fault. The features of fault currents are extracted by first level decomposition of the current samples using discrete wavelet transform (DWT) and the extracted features are applied as inputs to ELMs for fault section identification, classification and location. The feasibility of the proposed method has been tested on a 400 kV, 300 km series compensated transmission line for all the ten types of faults using MATLAB simulink. On testing 28,800 fault cases with varying fault resistance, fault inception angle, fault distance, load angle, percentage compensation level and source impedance, the performance of the proposed method has been found to be quite promising. The results also indicate that the proposed method is robust to wide variation in system and operating conditions.     

A unified framework for tree search decoding: rediscovering the sequential decoder

We consider receiver design for coded transmission over linear Gaussian channels. We restrict ourselves to the class of lattice codes and formulate the joint detection and decoding problem as a closest lattice point search (CLPS). Here, a tree search framework for solving the CLPS is adopted. In our framework, the CLPS algorithm is decomposed into the preprocessing and tree search stages. The role of the preprocessing stage is to expose the tree structure in a form matched to the search stage. We argue that the forward and feedback (matrix) filters of the minimum mean-square error decision feedback equalizer (MMSE-DFE) are instrumental for solving the joint detection and decoding problem in a single search stage. It is further shown that MMSE-DFE filtering allows for solving underdetermined linear systems and using lattice reduction methods to diminish complexity, at the expense of a marginal performance loss. For the search stage, we present a generic method, based on the branch and bound (BB) algorithm, and show that it encompasses all existing sphere decoders as special cases. The proposed generic algorithm further allows for an interesting classification of tree search decoders, sheds more light on the structural properties of all known sphere decoders, and inspires the design of more efficient decoders. In particular, an efficient decoding algorithm that resembles the well-known Fano sequential decoder is identified. The excellent performance-complexity tradeoff achieved by the proposed MMSE-DFE Fano decoder is established via simulation results and analytical arguments in several multiple-input multiple-output (MIMO) and intersymbol interference (ISI) scenarios.     

Impact of applying pre-processing techniques for improving classification accuracy

Image denoising is a procedure aimed at removing noise from images while retaining as many important signal features as possible. Many images suffer from poor contrast due to inadequate illumination or finite sensitivity of the imaging device, electronic sensor noise or atmospheric disturbances. This paper proposes a hybrid directional lifting technique for image denoising to retain the original information present in the images. The primary objective of this paper is to show the impact of applying preprocessing techniques for improving classification accuracy. In order to classify the image accurately, effective preservation of edges and contour details of an image is essential. The discrete wavelet transform-based interpolation technique is developed for resolution enhancement. The image is then classified using support vector machine classifier, which is well suitable for image classification. The efficiency of the classifier is analyzed based on receiver operating characteristic (ROC) curves. The quantitative performance measures peak signal to noise ratio and ROC analysis show the significance of the proposed techniques.     

Combustion analysis of the diesel–biogas dual fuel direct injection diesel engine – the gas diesel engine

In this investigation, biogas (BG) was used as an alternative fuel in a single-cylinder, four-stroke, air-cooled, direct injection (DI) diesel engine that was operated on a dual fuel mode. Biogas was produced from a non-edible seed de-oiled cake-pongamia pinnata (Karanja), which was collected from the biodiesel industries. The BG was inducted along with the air in suction of the engine at four different flow rates varying from 0.3?kg/h to 1.2?kg/h in steps of 0.3?kg/h. The investigation results revealed that BG inducted at a flow rate of 0.9?kg/h gives better combustion characteristics of engine behaviour than those of other flows throughout the engine operation. The ignition delay (ID) and combustion duration of the engine run by dual fuel operation at a BG flow rate of 0.9?kg/h were found to be longer by about 2 °CA and 2.9 °CA, respectively, in comparison with diesel at full load. The cylinder peak pressure was found to be overall higher by about 11?bar than that of diesel at full load.     

A novel prognosis and segmentation of necrosis (dead cells) in contrast enhanced T1-weighted glioblastoma tumor with automatic contextual clustering

In recent years, mortality rate with high-grade tumor has been increased significantly especially with glioblastoma (GBM) brain tumor while compared to other malignant brain tumor. Here, the amount of dead cells accommodated with the tumor tissue in GBM brain tumor play a vital task and necessitate an earlier diagnosis of malignancy with the GBM tumor. It inspires to implement new automatic diagnosis system which detects the dead cells and tumor tissue with the GBM brain tumor, such that the survival rate of the diseased can easily be prognosis by the Radiologist and Neurosurgeon. The main objective of this article is to detect the amount of dead cells with respect to tumor tissue associated with the GBM brain tumor which desires the impact factor of the brain tumor. In this framework, initially, the new contrast enhancement modality is incorporated to enhance the gray information over the dead cells and the tumor tissue with the T1-weighted MRI GBM brain tumor. In this enhancement, the edges of the tumor cells and its dead cells are magnified efficiently. As the noises and outliers with MR image is unpredictable and it experiences the variable amount of noises over the local window, the contextual information over each pixel of the image is adaptively modified with respect to the amount of noise over local window using adaptive contextual clustering. The performance evaluation of the framework is investigated which exhibits the overwhelming result compared to conventional detection techniques.     

Design and Characterization of a W-Band Folded-Waveguide Slow-Wave Structure

A single-section slow-wave structure for a W-band folded-waveguide traveling-wave tube with operating bandwidth of around 4% was designed for delivering the output power of 50 W at the operating voltage of 13.5 kV and operating beam current of 80 mA. The design was carried out using analytical formulations and 3D electromagnetic simulations. The beam-wave interaction analysis was carried out using large signal Lagrangian analysis and particle-in-cell simulation. The folded-waveguide slow-wave structure along with input-output couplers and RF windows were fabricated. Cold test measurements were carried out for dispersion characteristics of the slow-wave structure and voltage standing-wave ratio and insertion loss characteristics of the RF window. The measured cold circuit parameters show close agreement with the analysis.